code: def embeddable_image(data):
      img_data = 255 - 15 * data.astype(np.uint8)
      image = Image.fromarray(img_data, mode="L").resize(
          (64, 64), Image.BICUBIC
      )
      buffer = BytesIO()
      image.save(buffer, format="png")
      for_encoding = buffer.getvalue()
      return (
          "data:image/png;base64,"
          + base64.b64encode(for_encoding).decode()
      )
  
file_path: umap/doc/bokeh_digits_plot.py
imports: import numpy
  from sklearn.datasets import load_digits
  import pandas
  import umap
  from io import BytesIO
  from PIL import Image
  import base64
  from bokeh.plotting import figure, show, output_file
  from bokeh.models import HoverTool, ColumnDataSource, CategoricalColorMapper
  from bokeh.palettes import Spectral10
label_desc: Use image node_id 1 for calling a global function with example usage: embeddable_image(data) and returns: unknown